VIDA: A Dataset for Visually Dependent Ambiguity in Multimodal Machine Translation
Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous expression to its intended meaning. Although prior work has proposed disambiguation-oriented benchmarks probing the role of vision, we observe that existing benchmarks remain limited by task-format mismatch, narrow ambiguity coverage, or insufficient visual-dependency validation. Moreover, existing ambiguity evaluations are not well suited to diverse ambiguity types in open-ended translation. To address these limitations, we present VIDA (Visually-Dependent Ambiguity), a dataset of 2,500 carefully curated instances in which resolving an ann...
| Authors | Jingheng Pan, Xintong Wang, Longyue Wang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 3 May 2026 |
| Last updated at source | 5 October 2026 |
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